{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "#### seaborn scatter 散点图\n",
    "- seaborn.relplot(kind='scatter'): figure-level\n",
    "- seaborn.scatterplot():           axes-level"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "# 运动员参赛事件\n",
    "df1 = pd.read_csv('./input/athlete_events.csv')\n",
    "df2 = pd.read_csv('./input/noc_regions.csv')\n",
    "# 验证，保证右边表是1，避免右边重复，出现笛卡尔积的情况\n",
    "df = pd.merge(df1, df2, how='left',on='NOC', validate='m:1')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "   ID                 Name Sex   Age  Height  Weight     Team  NOC  \\\n0   1            A Dijiang   M  24.0   180.0    80.0    China  CHN   \n1   2             A Lamusi   M  23.0   170.0    60.0    China  CHN   \n2   3  Gunnar Nielsen Aaby   M  24.0     NaN     NaN  Denmark  DEN   \n\n         Games  Year  Season       City       Sport  \\\n0  1992 Summer  1992  Summer  Barcelona  Basketball   \n1  2012 Summer  2012  Summer     London        Judo   \n2  1920 Summer  1920  Summer  Antwerpen    Football   \n\n                          Event Medal   region notes  \n0   Basketball Men's Basketball   NaN    China   NaN  \n1  Judo Men's Extra-Lightweight   NaN    China   NaN  \n2       Football Men's Football   NaN  Denmark   NaN  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>ID</th>\n      <th>Name</th>\n      <th>Sex</th>\n      <th>Age</th>\n      <th>Height</th>\n      <th>Weight</th>\n      <th>Team</th>\n      <th>NOC</th>\n      <th>Games</th>\n      <th>Year</th>\n      <th>Season</th>\n      <th>City</th>\n      <th>Sport</th>\n      <th>Event</th>\n      <th>Medal</th>\n      <th>region</th>\n      <th>notes</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>A Dijiang</td>\n      <td>M</td>\n      <td>24.0</td>\n      <td>180.0</td>\n      <td>80.0</td>\n      <td>China</td>\n      <td>CHN</td>\n      <td>1992 Summer</td>\n      <td>1992</td>\n      <td>Summer</td>\n      <td>Barcelona</td>\n      <td>Basketball</td>\n      <td>Basketball Men's Basketball</td>\n      <td>NaN</td>\n      <td>China</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>A Lamusi</td>\n      <td>M</td>\n      <td>23.0</td>\n      <td>170.0</td>\n      <td>60.0</td>\n      <td>China</td>\n      <td>CHN</td>\n      <td>2012 Summer</td>\n      <td>2012</td>\n      <td>Summer</td>\n      <td>London</td>\n      <td>Judo</td>\n      <td>Judo Men's Extra-Lightweight</td>\n      <td>NaN</td>\n      <td>China</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>Gunnar Nielsen Aaby</td>\n      <td>M</td>\n      <td>24.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Denmark</td>\n      <td>DEN</td>\n      <td>1920 Summer</td>\n      <td>1920</td>\n      <td>Summer</td>\n      <td>Antwerpen</td>\n      <td>Football</td>\n      <td>Football Men's Football</td>\n      <td>NaN</td>\n      <td>Denmark</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 271116 entries, 0 to 271115\n",
      "Data columns (total 17 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ID      271116 non-null  int64  \n",
      " 1   Name    271116 non-null  object \n",
      " 2   Sex     271116 non-null  object \n",
      " 3   Age     261642 non-null  float64\n",
      " 4   Height  210945 non-null  float64\n",
      " 5   Weight  208241 non-null  float64\n",
      " 6   Team    271116 non-null  object \n",
      " 7   NOC     271116 non-null  object \n",
      " 8   Games   271116 non-null  object \n",
      " 9   Year    271116 non-null  int64  \n",
      " 10  Season  271116 non-null  object \n",
      " 11  City    271116 non-null  object \n",
      " 12  Sport   271116 non-null  object \n",
      " 13  Event   271116 non-null  object \n",
      " 14  Medal   39783 non-null   object \n",
      " 15  region  270746 non-null  object \n",
      " 16  notes   5039 non-null    object \n",
      "dtypes: float64(3), int64(2), object(12)\n",
      "memory usage: 37.2+ MB\n"
     ]
    }
   ],
   "source": [
    "# 通过其可以查看空值情况\n",
    "df.info()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 206853 entries, 0 to 271115\n",
      "Data columns (total 17 columns):\n",
      " #   Column  Non-Null Count   Dtype  \n",
      "---  ------  --------------   -----  \n",
      " 0   ID      206853 non-null  int64  \n",
      " 1   Name    206853 non-null  object \n",
      " 2   Sex     206853 non-null  object \n",
      " 3   Age     206165 non-null  float64\n",
      " 4   Height  206853 non-null  float64\n",
      " 5   Weight  206853 non-null  float64\n",
      " 6   Team    206853 non-null  object \n",
      " 7   NOC     206853 non-null  object \n",
      " 8   Games   206853 non-null  object \n",
      " 9   Year    206853 non-null  int64  \n",
      " 10  Season  206853 non-null  object \n",
      " 11  City    206853 non-null  object \n",
      " 12  Sport   206853 non-null  object \n",
      " 13  Event   206853 non-null  object \n",
      " 14  Medal   30196 non-null   object \n",
      " 15  region  206583 non-null  object \n",
      " 16  notes   3494 non-null    object \n",
      "dtypes: float64(3), int64(2), object(12)\n",
      "memory usage: 28.4+ MB\n"
     ]
    }
   ],
   "source": [
    "df_hw = df.dropna(\n",
    "    subset=['Height', 'Weight'], # 身高和体重的关系\n",
    "    how='any'\n",
    ")\n",
    "df_hw.info()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [],
   "source": [
    "sns.set(context='talk',\n",
    "        palette='husl')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6969 entries, 1 to 270988\n",
      "Data columns (total 17 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   ID      6969 non-null   int64  \n",
      " 1   Name    6969 non-null   object \n",
      " 2   Sex     6969 non-null   object \n",
      " 3   Age     6969 non-null   float64\n",
      " 4   Height  6969 non-null   float64\n",
      " 5   Weight  6969 non-null   float64\n",
      " 6   Team    6969 non-null   object \n",
      " 7   NOC     6969 non-null   object \n",
      " 8   Games   6969 non-null   object \n",
      " 9   Year    6969 non-null   int64  \n",
      " 10  Season  6969 non-null   object \n",
      " 11  City    6969 non-null   object \n",
      " 12  Sport   6969 non-null   object \n",
      " 13  Event   6969 non-null   object \n",
      " 14  Medal   1920 non-null   object \n",
      " 15  region  6969 non-null   object \n",
      " 16  notes   0 non-null      object \n",
      "dtypes: float64(3), int64(2), object(12)\n",
      "memory usage: 980.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# 筛选 'NOC' 中只有'CHN', 'USA', 'RUS' 三个国家；\n",
    "# 年大于2008年；对运动员进行去重\n",
    "df_hw = df_hw[df_hw['NOC'].isin(['CHN', 'USA', 'RUS'])]\n",
    "df_hw = df_hw[df_hw['Year'] >= 2008]\n",
    "df_hw.drop_duplicates(subset=['ID'])\n",
    "df_hw.info()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7fe105e12e50>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 挡住图形了\n",
    "sns.scatterplot(\n",
    "    x='Height',\n",
    "    y='Weight',\n",
    "    data=df_hw.sample(30),\n",
    "    hue='NOC',\n",
    "    style='Sex',\n",
    "    size='Age'\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% 语义\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "data": {
      "text/plain": "<seaborn.axisgrid.FacetGrid at 0x7fe1039b5310>"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 456.025x360 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 图例在右侧\n",
    "sns.relplot(\n",
    "    kind='scatter',\n",
    "    x='Height',\n",
    "    y='Weight',\n",
    "    data=df_hw.sample(30),\n",
    "    hue='NOC', # 颜色语义\n",
    "    style='Sex', # 三种语义，扩展维度，现在是五维的语义\n",
    "    size='Age' # 数值表示大小\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [
    {
     "data": {
      "text/plain": "<seaborn.axisgrid.FacetGrid at 0x7fe103ff11d0>"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1536.03x720 with 2 Axes>",
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(\n",
    "    kind='scatter',\n",
    "    x='Height',\n",
    "    y='Weight',\n",
    "    data=df_hw.sample(30),\n",
    "    hue='NOC',\n",
    "    style='Sex',\n",
    "    size='Age',\n",
    "    col='Season', # 横坐标显示\n",
    "    aspect= 1, # 宽/比高\n",
    "    height=10 # 每一个高度是72像素\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "pd.pivot_table\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "language": "python",
   "display_name": "Python 3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "3.7.6-final"
  },
  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
    "source": [],
    "metadata": {
     "collapsed": false
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}